CODEWITHSUNDEEP
pythonarrayspython-3.xnumpy
GeometricalFlows
GeometricalFlows

Reputation: 31

Python3 , Numpy -- Matrix of Matrix elements

I want to create a matrix that contains matrix elements. So I did the obvious thing and made this:

import numpy as np

A = np.array([1,2,3,1],[3,1,5,1])
B = np.array([1,6,8,9],[9,2,7,1])
E = np.array([A, B],[B, A])

But the compiler returns: TypeError: data type not understood

What can I do to create such a matrix, because I have really huge matrices and I dont have the time to explicitly write everyone down ?

* Edit 1: *

Additional problem that occurred:

enter image description here

Instead of getting a 14x14 matrix, I am getting a multidimensional (2,2,7,7) matrix. Where in the simplified version that was my original question , everything is sound. Any ideas why this occurs now?

In this case I have the Amat 7x7, Bmat 7x7 , Emat 14x14, Smat 14x14

Edit 2

Ok I solved the problem using the np.block() as it was stated in the comments below. Thank you very much.

Upvotes: 2

Views: 235

Answers (3)

maow
maow

Reputation: 2887

You were close, just missing a few brackets. For a matrix you need to give np.array a list of lists.

In [4]: import numpy as np
   ...: 
   ...: A = np.array([[1,2,3,1],[3,1,5,1]])
   ...: B = np.array([[1,6,8,9],[9,2,7,1]])
   ...: E = np.array([[A, B],[B, A]], dtype=int)
   ...: 

In [5]: E
Out[5]: 
array([[[[1, 2, 3, 1],
     [3, 1, 5, 1]],

    [[1, 6, 8, 9],
     [9, 2, 7, 1]]],


   [[[1, 6, 8, 9],
     [9, 2, 7, 1]],

    [[1, 2, 3, 1],
     [3, 1, 5, 1]]]])

Upvotes: 1

Mark Dickinson
Mark Dickinson

Reputation: 30561

Assuming that you want a two-dimensional array of shape (4, 8) as a result, it sounds as though you're looking for numpy.block. It's available since NumPy 1.13, and as the name suggests, it creates a new array out of blocks, where each block is an existing array.

You also need an extra pair of square brackets in the calls that create A and B. The signature of numpy.array is:

array(object, dtype=None, copy=True, order='K', subok=False, ndmin=0)

So if you write np.array([1, 2, 3, 1], [3, 1, 5, 1]) then you're passing two arguments to the array function, and the second argument will be interpreted as the dtype: i.e., the desired datatype of the elements of the array. This is why you're getting the "data type not understood" error. Instead, you want to pass a nested list-of-lists as the first argument: np.array([[1, 2, 3, 1], [3, 1, 5, 1]]).

Putting it all together:

>>> import numpy as np
>>> A = np.array([[1, 2, 3, 1], [3, 1, 5, 1]])
>>> B = np.array([[1, 6, 8, 9], [9, 2, 7, 1]])
>>> E = np.block([[A, B], [B, A]])
>>> A
array([[1, 2, 3, 1],
       [3, 1, 5, 1]])
>>> B
array([[1, 6, 8, 9],
       [9, 2, 7, 1]])
>>> E
array([[1, 2, 3, 1, 1, 6, 8, 9],
       [3, 1, 5, 1, 9, 2, 7, 1],
       [1, 6, 8, 9, 1, 2, 3, 1],
       [9, 2, 7, 1, 3, 1, 5, 1]])

Upvotes: 4

Andreas Storvik Strauman
Andreas Storvik Strauman

Reputation: 1655

and welcome to Stack Overflow!

The np.array wants the first argument to be the matrix and the second argument to be the datatype.

Here, you're actually sending in two lists as the first two arguments. Since a list of numbers is not a datatype, it does not understand what you're trying to do. You need to enclose it in a list:

import numpy as np

A = np.array([[1,2,3,1],[3,1,5,1]])
B = np.array([[1,6,8,9],[9,2,7,1]])
E = np.array([[A, B],[B, A]])

To send in a datatype, you could do e.g.

D = np.array([1,2,3,4,5], np.float32). Now the second argument is an actual datatype, and not a list.

Upvotes: 3

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